TY - JOUR
AU - Boivin,Jean
AU - Ng,Serena
TI - Understanding and Comparing Factor-Based Forecasts
JF - National Bureau of Economic Research Working Paper Series
VL - No. 11285
PY - 2005
Y2 - May 2005
DO - 10.3386/w11285
UR - http://www.nber.org/papers/w11285
L1 - http://www.nber.org/papers/w11285.pdf
N1 - Author contact info:
Jean Boivin
Bank of Canada
234 Wellington Street
Ottawa
Ontario K1A 0G9
Canada
Tel: 613-782-8278
E-Mail: jboivin@bankofcanada.ca
Serena Ng
Department of Economics
Columbia University
440 W. 118 St.
International Affairs Building, MC 3308
New York
NY 10027
Tel: 212-854-5488
E-Mail: serena.ng@columbia.edu
AB - Forecasting using `diffusion indices' has received a good deal of attention in recent years. The idea is to use the common factors estimated from a large panel of data to help forecast the series of interest. This paper assesses the extent to which the forecasts are influenced by (i) how the factors are estimated, and/or (ii) how the forecasts are formulated. We find that for simple data generating processes and when the dynamic structure of the data is known, no one method stands out to be systematically good or bad. All five methods considered have rather similar properties, though some methods are better in long horizon forecasts, especially when the number of time series observations is small. However, when the dynamic structure is unknown and for more complex dynamics and error structures such as the ones encountered in practice, one method stands out to have smaller forecast errors. This method forecasts the series of interest directly, rather than the common and idiosyncratic components separately, and it leaves the dynamics of the factors unspecified. By imposing fewer constraints, and having to estimate a smaller number of auxiliary parameters, the method appears to be less vulnerable to misspecification, leading to improved forecasts.
ER -